from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification

if __name__ == '__main__':
    X, y = make_classification(n_samples=1000, n_features=4,
                               n_informative=2, n_redundant=0,
                               random_state=0, shuffle=False)
    clf = RandomForestClassifier(max_depth=2, random_state=0)
    clf.fit(X, y)

    print(clf.predict([[0, 0, 0, 0]]))

# https://blog.csdn.net/u012102306/article/details/52228516
